Consciousness isn't an emergent property of computation. Instead, physical systems like brains—or potentially AI—act as interfaces. Creating a conscious AI isn't about birthing a new awareness from silicon, but about engineering a system that opens a new "portal" into the fundamental network of conscious agents that already exists outside spacetime.
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OpenAI co-founder Ilya Sutskever suggests the path to AGI is not creating a pre-trained, all-knowing model, but an AI that can learn any task as effectively as a human. This reframes the challenge from knowledge transfer to creating a universal learning algorithm, impacting how such systems would be deployed.
The popular conception of AGI as a pre-trained system that knows everything is flawed. A more realistic and powerful goal is an AI with a human-like ability for continual learning. This system wouldn't be deployed as a finished product, but as a 'super-intelligent 15-year-old' that learns and adapts to specific roles.
If reality is a shared virtual experience, then physical death is analogous to a player taking off their VR headset. Their avatar in the game becomes inert, but the player—the conscious agent—is not dead. They have simply disconnected from that specific simulation. This re-frames mortality as a change in interface, not annihilation.
Current self-driving technology cannot solve the complex, unpredictable situations human drivers navigate daily. This is not a problem that more data or better algorithms can fix, but a fundamental limitation. According to the 'Journey of the Mind' theory, full autonomy will only be possible when vehicles can incorporate the actual mechanism of consciousness.
To determine if an AI has subjective experience, one could analyze its internal belief manifold for multi-tiered, self-referential homeostatic loops. Pain and pleasure, for example, can be seen as second-order derivatives of a system's internal states—a model of its own model. This provides a technical test for being-ness beyond simple behavior.
Physicists are finding structures beyond spacetime (e.g., amplituhedra) defined by permutations. Hoffman's theory posits these structures are the statistical, long-term behavior of a vast network of conscious agents. Physics and consciousness research are unknowingly meeting in the middle, describing the same underlying reality from opposite directions.
An advanced AI will likely be sentient. Therefore, it may be easier to align it to a general principle of caring for all sentient life—a group to which it belongs—rather than the narrower, more alien concept of caring only for humanity. This leverages a potential for emergent, self-inclusive empathy.
Like a water nymph unable to imagine flight, our current consciousness limits our ability to foresee AI's transformative potential. This metaphor helps frame AI not as an incremental change but as a fundamental, reality-altering shift.
The reason we don't see aliens (the Fermi Paradox) is not because they are distant, but because our spacetime interface is designed to filter out the overwhelming reality of other conscious agents. The "headset" hides most of reality to make it manageable, meaning the search for physical extraterrestrial life is fundamentally limited.
Biological intelligence has no OS or APIs; the physics of the brain *is* the computation. Unconventional AI's CEO Naveen Rao argues that current AI is inefficient because it runs on layers of abstraction. The future is hardware where intelligence is an emergent property of the system's physics.
